Previously titled: ReactomeFIViz: the Reactome FI Cytoscape app for pathway and network-based data analysis
Previously titled: ReactomeFIViz: the Reactome FI Cytoscape app for pathway and network-based data analysis
复制标题
DOI：
--
复制
发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Guanming Wu;Eric T. Dawson;Adrian Duong;R. Haw;Lincoln Stein
中科院分区：
文献类型：
--
作者：
Guanming Wu;Eric T. Dawson;Adrian Duong;R. Haw;Lincoln Stein
高通量实验在现代生物学研究中是常规进行的。然而，从大量的实验数据中提取有意义的结果对生物学家来说是一项具有挑战性的任务。将数据投影到通路和网络环境中是一种强大的方法，可以解开看似分散的大型数据集中嵌入的模式，并帮助发现与癌症和其他复杂疾病相关的知识。我们开发了一个名为“ReactomeFIViz”的Cytoscape应用程序，该应用程序利用高度可靠的基因功能相互作用网络，结合来自Reactome和其他途径数据库的人类策划途径。该应用程序提供了一套功能，以帮助生物学家以生物直观和用户友好的方式执行基于路径和网络的数据分析。生物学家可以使用这个应用程序来揭示与他们的研究相关的网络和途径模式，从基因表达数据集中搜索基因签名，揭示由列表中的基因显著富集的途径，并使用概率图形模型将多个基因组数据类型整合到途径环境中。我们相信，我们的应用程序将为研究人员提供强大的力量，以分析固有的噪声高通量实验数据，以找到生物相关的信息。开放式同行评审
High-throughput experiments are routinely performed in modern biological studies. However, extracting meaningful results from massive experimental data sets is a challenging task for biologists. Projecting data onto pathway and network contexts is a powerful way to unravel patterns embedded in seemingly scattered large data sets and assist knowledge discovery related to cancer and other complex diseases. We have developed a Cytoscape app called “ReactomeFIViz”, which utilizes a highly reliable gene functional interaction network combined with human curated pathways derived from Reactome and other pathway databases. This app provides a suite of features to assist biologists in performing pathwayand network-based data analysis in a biologically intuitive and user-friendly way. Biologists can use this app to uncover network and pathway patterns related to their studies, search for gene signatures from gene expression data sets, reveal pathways significantly enriched by genes in a list, and integrate multiple genomic data types into a pathway context using probabilistic graphical models. We believe our app will give researchers substantial power to analyze intrinsically noisy highthroughput experimental data to find biologically relevant information. Open Peer Review